7 accepted papers
Motivated by the challenge of achieving rapid learning in physical environments, this paper presents the development and training of a robotic system designed to navigate and solve a labyrinth game using model-based reinforcement learning techniques. The method involves extracting low-dimensional ob…
This paper presents an offset-free model predictive controller for fast and accurate control of a spherical soft robotic arm. In this control scheme, a linear model is combined with an online disturbance estimation technique to systematically compensate model deviations. Dynamic effects such as mate…
Data-driven approaches to tactile sensing aim to overcome the complexity of accurately modeling contact with soft materials. However, their widespread adoption is impaired by concerns about data efficiency and the capability to generalize when applied to various tasks. This paper focuses on both the…
This paper presents a vision-based sensing approach for a soft linear actuator, which is equipped with an internal camera. The proposed vision-based sensing pipeline predicts the three-dimensional tip position of the actuator. To train and evaluate the algorithm, predictions are compared to ground t…
In recent years, ultra-wideband radio technology has become increasingly popular as a space-and cost-effective solution to the problem of indoor localization. This paper demonstrates how measurements of the channel impulse response can be used to estimate a signal's angle of arrival at a receiving a…
This paper presents the application of an iterative learning control scheme to improve the position tracking performance for an articulated soft robotic arm during aggressive maneuvers. Two antagonistically arranged, inflatable bellows actuate the robotic arm and provide high compliance while enabli…
Due to the complexity of modeling the elastic properties of materials, the use of machine learning algorithms is continuously increasing for tactile sensing applications. Recent advances in deep neural networks applied to computer vision make vision-based tactile sensors very appealing for their hig…